1. Field of the Invention
The invention relates to a method for monitoring plants with mechanical, in particular hydromechanical, components.
2. Description of the Prior Art
For industrial applications, for example, for the generation of electrical energy, complex plants which comprise a large number of components are often used. As a representative example reference is made in the following to a hydroelectric power plant in which turbines are driven by means of hydraulic force for the generation of electrical energy. In this example, the hydromechanical components are thus the turbines, which are set rotating by flowing water and which drive the generators.
From the points of view of safety and economy, it is very important to continuously monitor such plants and their components during operation in order to detect disturbances in the operation, that is, deviations from normal operating behavior, as early and reliably as possible. Often a plurality of parameters such as, for example, pressure, temperatures of the water at different positions in the plant, flow rates, speeds of rotation, powers, bearing temperatures etc., are determined by measurement and e.g., stored and/or graphically displayed as a function of time. Usually, however, components such as turbines do not operate at a fixed operating or working point, so that the temporal behavior of the measured values to be determined for monitoring exhibits pronounced fluctuations even in normal, that is, disturbance-free operation. Therefore, it is very difficult to judge on the basis of the temporal behavior of the measured values--if at all--whether the plant is operating correctly, free of disturbance. In addition, it is difficult to detect and to judge very slow temporal variations such as arise, for example, through operational wear.
In principle, it would indeed be possible to model the entire plant physically, that is, to calculate the physical relationships between the individual parameters, and then to perform an assessment of the operating state through a comparison between such physical model calculations and the values determined by measurement. In practice, however, this way is frequently too cost-intensive and laborious so that it is poorly suited for industrial applications in particular. One reason for this is that industrial plants have an enormous complexity with numerous components in mutual interaction so that a moderately reliable physical model must take a large number of relationships between the individual parameters into account, through which its generation becomes an extremely difficult, time consuming and cost-intensive task.
Therefore, it is customary in practice for the monitoring of the plant, in particular, for industrial applications, to predetermine fixed threshold values for several selected parameters, for example, the temperature in the bearing of a rotating shaft or the temperature of a coolant, on exceeding which an alarm is triggered or a warning is issued. This kind of monitoring has disadvantages however. There is namely the danger that operational disturbances or faults actually existent in the plant are overlooked or detected too late. Thus, it is possible, for example, that a bearing of a shaft or a seal has a defect, but that the monitored temperature does not exceed the threshold value required for triggering the alarm because the turbine is momentarily operating only at a low load. On the other hand, it is possible for false alarms to be triggered, for example, when the turbine briefly operates at a very high load, so that the threshold value required for triggering the alarm is exceeded with out a defect being present. A false alarm of this kind can lead to the plant being switched off without it actually being necessary, which is very disadvantageous, in particular, from the economic point of view.